System and a method of automatically sorting objects

ABSTRACT

This system relates to a system ( and a corresponding method ) of automatically sorting objects, wherein said system comprises a conveyor mechanism configured for conveying an object to a sorter device; a sensor device arranged such that the objects conveyed are caused to be located essentially within a predetermined reading space; and a calculator unit configured for receiving an electrical sensor signal representative of measurement data from said sensor device and configured for generating and emitting a control signal to said sorter device configured for sorting conveyed objects in response to/on the basis of said control signal, wherein said sensor signal is configured for detecting gamma radiation emitted from a conveyed object when exposed to a neutron flux with a given energy distribution, and configured for providing said sensor signal on the basis of said detection; and wherein said control signal is generated on the basis of said sensor signal. Hereby expedient and reliable automated sorting of objects is provided, wherein the frequency of erroneous sorting is dramatically reduced, the system using another and more reliable analysis method than was previously used. Moreover, the number of sorting errors is reduced to a level that is sufficient for complying with the requirements made with respect to the environment.

This invention relates to a system and a method of automatically sortingobjects, including objects contained in a flow of waste.

More specifically the invention relates to a system (and a correspondingmethod) comprising a conveyor mechanism configured for conveying anobject to a sorter device; a sensor device arranged such that the objectconveyed is caused to be located essentially within a predeterminedreading space; and a calculator unit configured for receiving anelectrical sensor signal representative of measurement data from saidsensor device and configured for generating and emitting a controlsignal to said sorter device configured for sorting conveyed objects inresponse to/on the basis of said control signal.

Often it is advantageous to be able to sort objects on the basis of anassociated class from a number of possible classes. Sometimes the amountof possible classes is limited to comprise only a few classes, such as‘metallic’ and ‘non-metallic’, eg when flows of environmentallyproblematic waste are to be sorted. In that case it is necessary to beable to determine common features for each sorted object belonging to aspecific class, said features relating the object to the given classdespite possible variations within each class.

Sorting of flows of material is extremely important in a large number ofproduction processes, and in the establishment of a socially viableeconomy of materials, the sorting of waste flows will play anincreasingly important part. Sorting may serve the purpose of egminimising or eliminating the presence of harmful substances inrecyclable flows of waste. Sorting may also be used in connection withon-line monitoring of outgoing flows from plants that treat householdwaste or particular types of waste, wherein the waste product, eg thesludge from combustion plants, needs to observe threshold values inrespect of several elemental substances in order to be suitable forrecycling or be deposited in the most inexpensive manner.

Sorting may also serve the object of ensuring a minimum concentration ofa desired component in connection with recycling.

Separation of materials in case of manual sorting is often erroneous incase of those flows of material, where the visual features of objectsare very similar, and furthermore this kind of sorting requiresconsiderable resources, eg in case of manual tasks. When waste sortingis concerned, where correct categorisation is of the utmost importanceprimarily for environmental considerations, such manual sorting with arisk of a high frequency of sorting errors is undesirable.

Sorting of eg pressure-impregnated timber from non-impregnated timber isnot a simple matter, as it may be an extremely difficult task todistinguish these two from each other, in particular as the timber agesand/or if the surface of the timber is coated.

Typically, two types of waste timber are dealt with that it is importantto distinguish between:

-   -   pressure-impregnated timber: typically this timber is        temporarily deposited as, to a wide extent, it contains large        amounts of heavy metals, such as copper, chrome, arsenic and        boron. At present there is no environmentally acceptable and        economically viable method of treating it.    -   non-pressure-impregnated timber: it can be disposed of by        incineration.

According to a survey (Iben V. Kristensen: Identifikation og sorteringaf affaldstræ vha. Farvereaktion (Identification and sorting of wastetimber by colour reaction), Workshop i Affaldsstrategier for imprægnerettræ (Workshop on waste strategies for impregnated timber) Borås2001-11-14) about 60% of unimpregnated waste timber was erroneouslycategorised as impregnated timber in manual sorting processes.Correspondingly about 16% of impregnated waste timber was erroneouslycategorised as unimpregnated timber.

This high percentage of errors is environmentally unacceptable, inparticular in the light of the circumstance that the amount ofimpregnated waste timber is expected to multiply in the next few yearsto come. As mentioned pressure-impregnated timber typically containsheavy metals such as cupper, chrome, arsenic and boron that areunacceptable pollutants.

Methods of chemically analysing an amount of heavy metal present in agiven object are known. However, it is inconvenient to apply such methodeg in the sorting of waste objects, since the amount of waste timber isincreased and such analysis is both time-consuming and economicallycumbersome.

It is therefore advantageous to provide a system by which objects can besorted in a simple, reliable, expedient and rational manner.

U.S. Pat. disclosure No. 4,830,193 concerns sorting lumps ofgold-bearing minerals by means of neutron activation analysis, whereingamma radiation and neutron irradiation occur at different times. Morespecifically the mineral lumps are sorted into two groups depending onsize and are irradiated, following which the intensity of gamma rays,having an energy of 297 KeV, is subsequently measured and eitheraccepted or rejected in response to the measured intensity at 297 KeV.

Patent No. GB 2 055 465 also relates to determination of the goldcontent of a material by use of neutron activation analysis, wherein thematerial is irradiated with neutrons and wherein the intensity of gammarays having an energy of 279 KeV (probably 297 KeV was intended) wassubsequently determined to achieve acceptance or rejection.

Patent No. EP 0 059 033 relates to sorting of ore, wherein ore isbombarded with neutrons by a number of irradiation units to formisotopes. The gamma radiation is detected—emitted by isotopes ofelements such as gold—by a number of detectors, thereby enablingidentification of the isotopes. It says that it is normally requiredthat all ore particles are subjected to at least substantially the sameamount of irradiation and a solution is provided.

It is therefore the object of the invention to provide a system that isable to efficiently, reliably and inexpensively classify objects with aview to sorting them on the basis of specific criteria by means of acontact-free and expedient sensor system.

This object is accomplished by a system of the kind mentioned above, andwherein said sensor device is based on Prompt Gamma-Neutron ActivationAnalysis (PGNAA) and comprises a neutron source configured for emittingneutrons; a moderator surrounding said neutron source and saidmeasurement space, and configured for moderating said emitted neutrons;and a detector configured for detecting gamma radiation emitted by anobject arranged within said measurement space when the object is exposedto a neutron flux with a given energy distribution; and generation ofsaid electrical sensor signal on the basis of said detection; andwherein said control signal is generated on the basis of said sensorsignal.

Hereby expedient and reliable automated sorting of objects is provided,whereby the frequency of erroneous sorting is dramatically reduced, thesystem using another and more reliable analysis method than waspreviously used. A system according to the invention presents theadvantage that, in addition to being automated, the number of sortingerrors is reduced to a level that is sufficient for complying with therequirements made with respect to the environment.

Typically a system according to the invention may multiply the number ofprocessed objects compared to previous methods.

The sorting system may be configured eg for sorting timer intoheavy-metal-containing timber or non-metal-containing timber,respectively. Alternatively the sorting system may be configured forsorting plastics into PVC-containing plastics or PVC-free plastics.

According to an alternative embodiment said sensor device furthercomprises a gamma shield and/or a neutron shield, wherein said gammashield is located between said source and said measurement space, and/orwherein said neutron shield is located between said detector and saidmeasurement space.

Hereby a minimisation of the flux of thermal neutrons into the detectoris obtained due to the neutron shield/screen which causes a dampening ofthe measured noise level.

According to a preferred embodiment, said sensor device furthercomprises a gamma shield arranged around said neutron source, therebyminimising direct radiation of gamma from the neutron source to saidneutron source.

According to one embodiment said sorting system is configured forsorting a flow of waste.

According to a preferred embodiment said detection is accomplishedcontact-free in relation to the object. Hereby a reduction in operatingcosts is achieved due ia to the minimal wear that occurs in connectionwith a touch-free embodiment and economies in respect of manual labour.

According to one embodiment an estimate is provided of the amount ofsample material in said measurement space on the basis of gammaradiation of an elemental substance, eg hydrogen, aluminium, silicon oriron, present in the sample material in a known concentration.

The described sensor technology is designated Prompt Gamma NeutronActivation Analysis (PGNAA) and is a well-known technique.

By PGNAA the object is irradiated with neutrons with relatively lowkinetic energy (so-called thermal neutrons) from a suitable source,whereby the cores of the elemental substances become unstable andimmediately fall back to a state of reduced energy while emitting gammaradiation with a characteristic energy.

More specifically, a reaction between an atomic nucleus and a thermalneutron is designated neutron capture and results in the nucleuschanging atomic weight corresponding to the mass of the neutron. Thisprocess will leave the nucleus in an excited/energy-rich state, fromwhich it decays momentarily while emitting gamma radiationcharacteristic of the nucleus in question. This gamma radiation isdesignated ‘prompt gamma’ as it is emitted momentarily.

Both neutrons and the resulting gamma radiation are very penetrating andit follows that even massive objects can often be analysed in acontact-free manner.

A Prompt Gamma Neutron Activation Analysis (PGNAA) method is based onthe fact that all elemental substances can react with low-energeticneutrons, the so-called ‘thermal neutrons’.

The various elemental substances have very different capacities when itcomes to reacting with thermal neutrons. This capacity is designated bya value typically designated the reactive cross section which varies bymore than 11 value factors throughout the periodic table of theelemental substances without apparent systematics.

Apart from the reactive cross section, the sensitivity to PGNAA of agiven elemental substance varies, on the one hand, with the amount andkind of the emitted gamma radiation and, on the other, with the natureof the detector system.

This analysis technique is well-suited for detecting treated objectsthat are not readily visually distinguishable, such aspressure-impregnated timber, as it is possible, on the one hand, tomeasure through voluminous objects such as posts and poles relativelyunaffected by surface layers such as paint and, on the other, whereinelemental substances such as cupper, chrome, arsenic and boron have suchhigh reactive cross-sections that a determination of the concentrationsseems to be possible.

As far it is known, practical use of PGNAA has been restricted tocharacterisation of coal in power plants, ore within the mining industryand raw-material mixtures for cement furnaces and the like. Theinvention shows how PGNAA can also be used for sorting waste.

Typically an embodiment is used, wherein said sensor device primarilyuses hydrogen as moderator due to the high moderator effect of hydrogen.

According to an alternative embodiment said sensor device primarilycomprises carbon material as moderator (rather than hydrogen). Thescattering cross section of carbon and hence its performance asmoderator is smaller than the performance of hydrogen; however, carbonhas a far smaller absorption cross section, which yet again entailsimproved utilisation of neutrons and considerably less noise in the formof undesired gamma radiation. Also the use of a hydrogen-poor moderatorenables an almost direct measurement of the hydrogen content of theobject, on the basis of which an estimate of the amount of timber in thereading space can be calculated; this part measurement being necessaryfor determining the concentration within an object.

According to one embodiment the system is configured for receivingmeasurements of objects of a known classification; and wherein theclassification unit comprises means for calculating weight factors of anumber of weighted sums established by a multivariable data analysis,calibration on an, iterative method by which an incremental refiningsuccessively provides an improved set of weight factors.

According to an alternative embodiment, said control signal is providedby the classification unit on the basis of signals comprising saidweight factors and said sensor signal.

According to one embodiment said sensor signal comprises a gamma spectrerepresenting recorded gamma radiation intensity within a givenphoton/energy range.

According to one embodiment said control signal (307) is provided on thebasis of the difference between a sensor signal (306) and apredetermined reference spectre obtained with empty measurement space(6) and stored in a memory unit (403).

The invention also relates to a method of automatically sorting objects,wherein the method comprises

-   -   conveying at least one object to a sorter device;    -   wherein said conveyance causes conveyed objects to be        essentially within a predetermined reading space of a sensor        device; and    -   receiving an electrical sensor signal representing measurement        data in a calculator unit/classification unit from said sensor        device and generating and emitting a control signal to said        sorter device configured for sorting objects on the basis of        said control signal;        wherein the method further comprises    -   emitting neutrons from a neutron source in said sensor device;    -   moderating said emitted neutrons by means of a moderator in said        sensor device, wherein said moderator surrounds said neutron        source and said measurement space;    -   detecting, on the basis of Prompt Gamma-Neutron-Activation        Analysis (PGNAA) by a detector in said sensor device, gamma        radiation emitted from an object within said measurement space        when it is exposed to a neutron flux with a given energy        distribution, and providing said sensor signal in said sensor        device on the basis of said detection; and    -   generating said control signal on the basis of said sensor        signal.

According to one embodiment the method comprises minimisation of theflux of thermal neutrons into the detector by means of a gamma shieldand/or a neutron shield in said sensor device; wherein said gamma shieldis arranged between said source and said measurement space and/orwherein said neutron shield is arranged between said detector and saidmeasurement space.

According to one embodiment the method comprises further minimisation ofdirect gamma radiation from the neutron source to said detector by meansof a gamma shield arranged around said neutron source in said sensordevice, such that radiation of gamma rays from source to detector isattenuated.

According to one embodiment the method comprises sorting of a flow ofwaste.

According to one embodiment said detection is performed contact-freewith respect to the object.

According to one embodiment an estimate is provided of the amount ofsample material in said measurement space on the basis of gammaradiation of an elemental substance, eg hydrogen, aluminium, silicon oriron, present in the sample material in a known concentration.

According to one embodiment said sensor device primarily comprisescarbon material as moderator.

According to one embodiment the method comprises receipt of measurementsof objects of a known classification and calculation of weight factorsof a number of weighted sums established by a multivariable dataanalysis, calibration or an iterative method by which incrementalrefining successively brings about an improved set of weight factors.

According to one embodiment the method further comprises that saidcontrol signal is provided by the classification unit on the basis ofsignals comprising said weight factors and said sensor signal.

According to one embodiment cluster analysis is used as a step inautomatically generating suggestions for categorising sample objects onthe basis of patterns in measurement data corresponding to said objects.

According to an embodiment said sensor signal comprises a gamma spectrerepresenting registered gamma radiation intensity within a givenphoton/energy range.

According to one embodiment said control signal (307) is provided on thebasis of the difference between a sensor signal (306) and apredetermined reference spectre received with empty measurement space(6) and stored in a memory unit (403).

The method according to the invention and embodiments thereof correspondto the system according to the invention and embodiments thereof andpresent the same advantages for the same reasons.

The invention will now be explained in further detail in the followingwith reference to the drawing; wherein

FIG. 1 schematically illustrates a cross section of an embodiment of asensor device according to the invention;

FIG. 2 schematically illustrates a cross-section of an alternativeembodiment of a sensor device according to the invention;

FIG. 3 illustrates an embodiment with conveyor mechanism, sensor andsorter device and a classification unit.

FIG. 4 shows an embodiment of a classification unit according to theinvention;

FIG. 5 shows examples of PGNAA spectres.

FIG. 1 schematically illustrates a cross section of a part of anembodiment of a sensor device (302) according to the invention andcomprising a neutron source (2), a moderator (4), a measurement space(6), a gamma shield (3), a neutron shield/a neutron screen (10) and adetector/sensor (8).

The neutron source (2) emits a neutron flux, ie neutrons with highkinetic energy, and is surrounded by a moderator (4) that serves thepurpose of moderating the neutrons to thermal velocities. The moderator(4) comprises a massive volume of a material having a large content of anumber of elemental substances (eg hydrogen and carbon) with highscattering cross-sections such as paraffin, polyethylene, graphite orwater. In the moderator (4) there is thereby formed an area containingthermal neutrons that will, following a number of scatterings, no longerhave a predominant direction. In this embodiment, the measurementspace/the three-dimensional measurement area (6) has a well-definedvolume/space within which a uniform and high neutron flux is establishedthrough a convenient shaping of the moderator (4) which typically, to alarge or small extent, surrounds said measurement space (6). Themeasurement space (6) may have many different configurations, egdepending on the relevant objects to be sorted.

The detector (8) that captures gamma radiation emitted by objectsarranged within the measurement space (6) will typically be sensitive toboth thermal neutrons and gamma radiation emitted by the neutron source(2) and the moderator (4) and radiation from natural nucleides in thesurroundings of the sensor device. Preferably both gamma (3) and neutronshielding (10) materials will be arranged in convenient places withinthe reading area. The detector (8) may eg be of the scintillation type,eg tallium-doted sodium-iodide; but it may also be of other types, egthe semi-conductor type. The latter detectors, however, typicallypresuppose a cooling, eg by means of liquid nitrogen, which makespractical use thereof rather difficult.

In practice all neutron sources, such as isotope or accelerator-basedsources, emit almost exclusively neutrons with high kinetic energy(within a range 10⁶-10⁷ eV). To attain thermal neutrons (kinetic energyof a range of 0,025 eV) the source is surrounded by the moderator (4)that consists of a material of a high scattering cross-section and a lowabsorption cross section. Preferably the moderator consists ofhydrogen-containing materials, such as water, paraffin or polyethylene,etc. In such moderator a neutron will, during its lifetime within thematerial, scatter elastically several times and, as describedpreviously, it will lose energy at each collision until the energy levelcorresponds to the thermal movement of the moderator's atoms.

Preferably a moderator material is used that primarily contains carboninstead of hydrogen. The scattering cross section of carbon and henceits performance as moderator is smaller than the performance ofhydrogen; however, carbon has a far smaller absorption cross sectionwhich, in turn, means that an improved neutron utilisation isaccomplished and far smaller noise in the form of undesired gammaradiation. Additionally the use of a hydrogen-poor moderator enables analmost direct measurement of the hydrogen content of the object, on thebasis of which an estimate of the amount of material (eg plastics ortimber) contained in the reading space can be calculated, as this partmeasurement is requisite in order to enable determination of theconcentration of an object.

Following initial processing of a number of detecting events collectedby the detector (8) in a number of gamma ranges within a predeterminedtime, these data are subjected to a transformation; weighted sums of theset of measurement variables being provided. For a PGNAA sensor eachindividual variable is constituted of the number of obtained detectorevents per time unit within a given gamma-quantum-energy range. Theweight factors for calculating the weighted sums can be provided bymultivariable regression analysis, by calibration or by iterativemethod, by which an improved set of weight factors is accomplished byincremental refining. Multivariable analysis is based on an approach tomulti-data characterised in that underlying variation patterns areidentified and used by means of methods known from mathematicalstatistics. For instance, signals from PGNAA sensors are multivariable,as the individual signal is present as a plurality of variables. Forcalibration, measurements of sets of objects having known classificationcan be used. A reference point in a multidimensional space of a numberof dimensions corresponding to the number of measurement variables isassociated with each individual class or classification. The individualreference point can be calculated as the average of the measurementpoints representing the objects belonging to the relevant class.

PGNAA can be utilised for a contact-free in-depth elemental substanceanalysis of eg waste or recycling material. Neutrons as well as theresulting gamma radiation measured by the detector system being verypenetrating, even solid objects can often be analysed contact-free bythis method. Since contact-free systems do not suffer from the samedegree of wear as is the case with non-contact-free systems, it istherefore desirable to use contact-free systems for an application suchas eg waste sorting, since very often the objects to be analysed consistof fragments of very varying shapes. Moreover the rate at which a flowof objects can be processed can typically be increased.

The measurement signal for a given object is preferably defined as thesimultaneous change of all variables detected when an object is conveyedthrough the reading space and subsequently measured during a timeinterval relative to a measurement with an empty measurement space.Overall, the information on the basis of which the classificationunit-is to conclude is described as a vector consisting of a sequence ofnumerical values.

Ideally a given elemental substance in the measurement space will giverise to a measurement signal of a given pattern and proportional withthe amount of the relevant elemental substance. The overall measurementsignal is then the sum of these contributions.

FIG. 2 schematically illustrates a cross-section of a part of analternative embodiment of a sensor system according to the invention.The neutron source (2) and a gamma shield (5), eg a lead shield, aroundsame is arranged such that direct radiation of gamma from the neutronsource (2) is minimised. The measurement space (6) is located close tothe source where the neutron flux is high and a comparatively thickmoderator material (4) between the detector (8) and the source (2) and aneutron shield (10) minimise the flux of intermediate neutrons into thedetector (8) which causes an attenuation of the measured noise level.

FIG. 3 illustrates an embodiment of the system according to theinvention comprising a conveyor mechanism (301), a sensor (302), asorter device (304) and a classification unit (303). Preferably, inaddition to the described sensor device (302), the system comprises aconveyor mechanism (301) for conveying objects (208) to and from themeasurement space/reading area (6); adetermination/calculation/classification unit (303) for processingmeasurement data from the sensor device (302) and determining to whichfraction/group a given object (308) belongs; and a sorter device (304)for sorting objects (308) on the background of the decisions of thecalculation/classification unit (303). A sorting object (308) may eg bewaste to be sorted, optionally with a view to recycling and/or expedientfurther processing.

For each object (308), the decision system (303) determines to whichgroup it belongs based on data/information received from the sensordevice (302) preferably in the form of measured gamma radiation such aseg number of recorded quanta and their energy distribution.

Alternatively the system may comprise one or more further sensors,wherein the calculation/classification unit (303) is further configuredfor receiving and processing data originating from such other sources.The further sensors(s) may be eg sensors for temperature measurement,measurement of neutron flux within the measurement space, gammadensiometry of objects, weighting cells, image-forming sensors (eg“vision”—TV camera+frame grabber), image-forming x-ray scan or othertypes of sensors (not shown).

According to one embodiment the calculator unit (303) is configured forcalculating concentrations of relevant elemental substances, which mayoccur on the basis of an estimate of the sampled amount. Given thesample material contains a well-defined concentration of hydrogen, egwater, plastics or timber, this estimate may be provided by use of ahydrogen-poor moderator that enables an almost direct measurement of thehydrogen contents of an object, on the basis of which an estimate of theamount of object (eg amount of timber) in the reading space could bedetermined with useful accuracy. The estimated amount of object can thenbe used to estimate the current concentration of the elementalsubstances. In general an estimate of the amount of sample material insaid measurement space is provided on the basis of gamma radiation of anelemental substance, eg hydrogen, aluminium, silicon or iron, present inthe sample material in a known concentration.

The decision system is explained and disclosed in further detail in thecontext of FIG. 4.

The conveyor mechanism (301) is able to advance objects (308) by meansof a conveyor belt, knob belt or the like, pushing or pullingmechanisms, pneumatic conveyance or the like, seizing or guidingmechanisms (including robot systems), etc.

The sorter mechanism/sorter device (304) may for instance be realised asbelt or guiding mechanism (eg a funnel device) that changes direction,as ejector with arm or jet of air or other medium, seizing mechanisms(including robot systems), etc.

In one embodiment where the conveyance mechanism (301) is a seizingmechanism (including robot), the conveyor (301) and sorter mechanism(304) may be one and the same.

A system according to the invention can be used eg for sortingpressure-impregnated timber from other timber, sorting PVC from otherplastics materials, etc.

FIG. 4 shows an embodiment of a classification unit (303) according tothe invention comprising one or more microprocessors (402) and/or one ormore digital signal processors (406); a memory unit (403) and means forreceiving and emitting signals (404) connected via a common data/addressbus (405). The microprocessor(s) (402) and/or the number of digitalprocessors (406) interact with the memory unit (403) and the means forreceiving/emitting signals (404). The means for receiving and emittingsignals (404) are responsible for communication with the number ofavailable sensors, including the sensor device (302) and userinterfaces, if any. The communication between the classification unit(303) and external units such as the sensor device (302), the sorterdevice (304), etc, may occur eg by means of IrDa, Bluetooth, IEEE802.11, wireless LAN, etc. but it may also be executed by means ofconventional permanent links. The memory unit (403) may store relevantinformation such as a dedicated computer programme and classificationvariables, calibration data, processing algorithms, etc. The memory unit(403) preferably comprises volatile and/or non-volatile memory units,such as ROM, RAM, magnetic memory, optical memory and combinationsthereof.

Processing of data may also be comprised in one single multi-functionalprocessor. The use of multi-functional processors instead of dedicateddigital signal processors may be advantageous in connection with someembodiments. Albeit digital signal processors are extremely suitable forhandling signal calculation in a system, most embodiments also require amicroprocessor for other tasks such as memory handling, userinteraction, etc. Therefore it may be advantageous to use amulti-functional processor which is capable of performing all of thementioned task types in order to thereby reduce the number of componentsand to minimise the power consumption and production costs, etc.Reduction of the number of processors to one will also mean that fewersets of instructions are to be mastered during the development of thisclassification unit.

Data from a PGNAA analysis are in the form of gamma spectre andpreferably the difference between a reference spectre recorded withempty measurement space (stored in memory unit (403)) and a relevantspectre provided via the sensor device is used. This difference isprocessed by the calculator unit(s) (402; 404) with a view todetermining a class for the relevant object.

Preferably the measurement signal/sensor signal from the detectorcomprises a gamma spectre per measurement (alternatively it is an optionto mediate across a number of spectres in order to reduce noise). Suchspectre may consist of eg 1024 integers, where the spectre representsthe number of recorded events (ie gamma radiation intensity) within agiven photon-energy-range (see eg FIG. 5). The observedpatterns/profiles are specific to the individual elemental substance. Incase a number of elemental substances are present in the measurementspace, the pattern/profile for each elemental substance will be added,preferably to the relative amount of the relevant elemental substanceand the absolute sensitivity of the apparatus relative thereto.

Since, typically, there will always occur slight variations in theinternal amplification of the detector, offsets of the observed spectrawill occur. To remedy this, a correction can be performed on the basisof identified known constant and invariant peaks. Moreover measurementcan be corrected in the event of decay of the neutron source during themeasurements.

According to a preferred embodiment, spectres are split into a smallernumber of windows to limit the number of variables and to reduce randomnoise.

The window splitting involves a reduction of the random noise whileconserving as much multivariable signal as possible. As opposed to this,splitting into a few windows reduces the most noise, while many windowsconserves the most of the multivariable signal. Since both measurementsare critical to a good data analysis, the determination of the optimalnumber of windows is important. The optimal number and the positions ofthe windows depend on the relevant task, ie which set of possibleelemental substances is to be analysed in the relevant embodiment. Ageneral example of a splitting of spectres with 1024 integers issplitting into ten windows covering the gamma field 2-10 MeV.

Alternatively other methods can be used for recognizing the amount ofelemental substances contained in a given object. These other methodscan use eg neural networks, other pattern-recognition procedures, etc.

FIG. 5 shows examples of PGNAA spectres. The spectre depicts thedistribution of gamma energy against the intensity of a given energy,the horizontal axis of the spectre being divided into 1024 channels,such that each channel corresponds to 10 KeV, and the number of recordedrecordings per second in the relevant channel is depicted in thevertical axis of the spectre. A peak around channel 225 thus correspondsto a gamma energy of 2.25 MeV.

-   -   Spectre 1 (501) shows a detector signal from an empty        measurement space. The prominent peak around 2.25 MeV is caused        by prompt gamma from capture of neutrons in the hydrogen in an        approximately 30-kilo heavy moderator of polyethylene. The low        signals primarily consist of scattered radiation from this peak.    -   The energy range from 2.5 MeV to 10 MeV is seen to contain only        very little signal. This very important signal range is        increased in spectre 2 (502).    -   Spectres 3, 4, 5 and 6 (503, 504, 505, 506) show in same        sectional view and energy range differences for empty        measurement space and 299 g of PVC, 234.7 g of copper, 27.4 g of        chrome or 31.8 g of arsenic, respectively, within the        measurement space. Thus these spectres represent typical        measurement signals wherein the peaks observed on the spectres        are characteristic for the elemental substance in question.

For each of substances Cu, Cr, Ar and Cl measurements were performed ona number of model objects, wherein the only significant signal-emittingelemental substance was one of the mentioned ones. Then, bymultivariable regression analysis a predictor (a function for indicatingthe contents) was calculated for each these elements. The predictor wascalculated on the basis of the total measurement sequence, as elementalsubstances other than the relevant ones are then considered asinterferences.

The predictors are robust as they are simultaneously and independentlyof each other able to predict the amount of the individual elementalsubstances. In the determination of the elemental substances inquestion, levels of significance were determined. Levels of significanceare calculation factors that partake in the estimation of theperformance of a full-scale plant.

The levels of significance can be determined as the ratio between thesignal magnitude and the standard deviation on the background. Thesignal is determined on the basis of the difference between the averageof the predictors for reference object and all of the samples. As thestandard deviation on the background the observed one is used on all ofthe samples for the current predictor.

On the basis of a calibration—in the current case to be understood as anestablishment of a prescription for how a measurement signal isconverted into a classification—the system is able to determine and sortan object within a given category. The calibration is validated tosearch for the ability to classify new measurement data. If the systemis unable to identify the difference necessary for the classification inrelation to proximate classes, said calibration may result in a negativeacceptance, whereby the system is able to eg report to which objects orclasses the problems relate. These objects may then optionally besubjected to renewed measurement, or the classification problem can bereformulated to the effect that the object classes the system is havingproblems distinguishing are combined.

It applies to all object classes that a more comprehensive calibration,ie more objects, more elemental substances, more measurements, etc, willmost likely increase the levels of significance. This will apply inparticular to arsenic, where the determination clearly suffers from lackof spectral information and improved suppression of interferences.

Due to the elevated absorption cross-section and characteristic emissionspectre of Cl in combination with the contents of chlorine in PVC beingtypically about twice the magnitude of the content of elementalsubstances of interest in pressure-impregnated timber, touch-freesorting of plastics in a PVC-containing and PVC-free fraction,respectively, will thus be considered to constitute a technology thatcould be implemented in a system according to the invention. Thussorting of other types of waste flows could also benefit from thepresent invention.

Automatic categorisation is a substantial element during theconstruction of a self-calibrating and user-friendly analysis plant;such plant having to be able to be calibrated by means of a set ofobjects that combine to represent the scattering that may occur duringmeasurement. Following a number of completed sample measurements thesystem comes up with a suggested sort key that is refined interactivelyin cooperation with an operator.

Examples of automatic calibration include a so-called cluster analysisperformed on a five-dimensional set of data consisting of predictionsfor Cu, Cr, As, Cl and B.

Cluster analysis is a technique for organising a number of points in apiece of timber, whereby the points that are most proximate each otherare most proximate in the timber. A cluster analysis presupposes that,to each point, a position is associated in an n-dimensional space, andthat this space is associated with a distance code, whereby the term‘distance’ makes sense. The analysis is performed by identifying the twomost proximate points in a data set. They are replaced and form a nodeto which the halfway position between the two points is allocated. Nowthe node replaces the two original points in the data set. The processis repeated until only one node remains.

1. A system of automatically sorting objects, wherein said systemcomprises: a conveyor mechanism (301) configured for conveying at leastone object (308) to a sorter device (304); a sensor device (302)arranged such that conveyed objects (308) are caused to be locatedessentially within a predetermined reading space (6); and acalculator/classification unit (303) configured for receiving anelectrical sensor signal (306) representing measurement data from saidsensor device (302) and configured for generating and emitting a controlsignal (307) to said sorter device (304) configured for sorting conveyedobjects (308) on the basis of said control signal (307), characterisedin that said sensor device is based on Prompt Gamma-Neutron ActivationAnalysis (PGNAA) and comprises a neutron source (2) configured foremitting neutrons; a moderator (4) surrounding said neutron source (2)and said measurement space (6), and configured for moderating saidemitted neutrons; and a detector (8) configured for detecting gammaradiation emitted by an object (308) arranged within said measurementspace (6) when the object (308) is exposed to a neutron flux with agiven energy distribution, and generation of said electrical sensorsignal (306) on the basis of said detection; and that said controlsignal (307) is generated on the basis of said sensor signal (306).
 2. Asystem according to claim 1, characterised in that said sensor device(302) further comprises a gamma shield (3) and/or a neutron shield (10),wherein said gamma shield (3) is located between said source (2) andsaid measurement space (6) and/or wherein said neutron shield (10) isarranged between said detector (8) and said measurement space (6).
 3. Asystem according to claim 1 or 2, characterised in that said sensordevice (302) further comprises a gamma shield (5) arranged around saidneutron source (2) such that direct radiation of gamma from the neutronsource (2) to said detector (8) is minimised.
 4. A system according toclaim 1, characterised in that said sorting system is configured forsorting a flow of waste.
 5. A system according to claim 1, characterisedin that said detection is performed contact-free with regard to theobject (308).
 6. A system according to claim 1, characterised in that anestimate of the amount of sample material in said measurement space (6)is provided on the basis of gamma radiation of an elemental substance,eg hydrogen, aluminium, silicon or iron, present in the sample materialin a known concentration.
 7. A system according to claim 1,characterised in that said sensor device primarily comprises carbonmaterial as moderator.
 8. A system according to claim 1, characterisedin that the system is configured for receiving measurements of objectswith a known classification; and that the classification unit (303)comprises means for calculating weight factors of a number of weightedsums established by multivariable data analysis, calibration oriterative method, by which an improved set of weight factors issuccessively attained by incremental refining.
 9. A system according toclaim 8, characterised in that said control signal (307) is provided bythe classification unit (303) on the basis of signals comprising saidweight factors and said sensor signal (306).
 10. A system according toclaim 1, characterised in that cluster analysis is used as a step inautomatic generation of suggestions for categorising sample objects onthe basis of patterns in measurement data corresponding to said objects.11. A system according to claim 1, characterised in that said sensorsignal (306) comprises a gamma spectre representing registered gammaradiation intensity within a given photon/energy range.
 12. A systemaccording to claim 1, characterised in that said control signal (307) isprovided on the basis of a difference between a sensor signal (306) anda predetermined reference spectre obtained with empty measurement space(6) and stored in a memory unit (403).
 13. A method of automaticallysorting objects wherein said method comprises conveying at least oneobject (308) to a sorter device (304); wherein said conveyance causesconveyed objects to be essentially within a predetermined reading space(6) of a sensor device (302); receiving an electrical sensor signal(306) representing measurement data in a calculator unit/classificationunit (303) from said sensor device (302); and generating and emitting acontrol signal to said sorter device (304) configured for sortingconveyed objects (308) on the basis of said control signal (307);characterised in that the method further comprises emitting neutronsfrom a neutron source (2) in said sensor device (302); moderating saidemitted neutrons by means of a moderator (4) in said sensor device(302), wherein said moderator (4) surrounds said neutron source (2) andsaid measurement space (6); detecting, on the basis of PromptGamma-Neutron-Activation Analysis (PGNAA) by a detector (8) in saidsensor device (302), gamma radiation emitted from an object (308) withinsaid measurement space (6) when it is exposed to a neutron flux with agiven energy distribution, and providing said sensor signal (306) insaid sensor device (302) on the basis of said detection signal (306);and generating said control signal (307) on the basis of said sensorsignal (306).
 14. A method according to claim 13, characterised in thatthe method comprises minimisation of the flow of thermal neutrons intothe detector by a gamma shield (3) and/or a neutron shield (10) in saidsensor device (302), wherein said gamma shield (3) is located betweensaid source (2) and said measurement space (6) and/or wherein saidneutron shield (10) is arranged between sad detector (8) and saidmeasurement space (6).
 15. A method according to claim 13, characterisedin that the method further comprises minimisation of direct radiation ofgamma from the neutron source (2) to said detector (8) of a gamma shield(5) arranged around said neutron source (2) in said sensor device (302).16. A method according to claim 13, characterised in that the methodcomprises sorting of a flow of waste.
 17. A method according to claim13, characterised in that said detection is performed contact-free withrespect to the object (308).
 18. A method according to claim 13,characterised in that an estimate of the amount of sample material insaid measurement space (6) is provided on the basis of gamma radiationof an elemental substance, eg hydrogen, aluminium, silicon or iron,present in the sample material in a known concentration.
 19. A methodaccording to claim 23, characterised in that said sensor deviceprimarily comprises carbon material as moderator.
 20. A method accordingto claim 13, characterised in that the method comprises receipt ofmeasurements of objects of a known classification; and that theclassification comprises means for calculating weight factors of anumber of weighted sums established by a multivariable data analysis,calibration or an iterative method by which an incremental refiningsuccessively brings about an improved set of weight factors.
 21. Amethod according to claim 20, characterised in the method furthercomprises that said control signal (307) is provided by theclassification unit (303) on the basis of signals comprising said weightfactors and said sensor signal (306).
 22. A method according to claim13, characterised in that the cluster analysis is used as a step inautomatically generating suggestions for categorising sample objects onthe basis of pattern in measurement data corresponding to these objects.23. A method according to claim 13, characterised in that said sensorsignal (306) comprises a gamma spectre representing registered gammaradiation intensity within a given photon/energy range.
 24. A methodaccording to claim 13, characterised in that said control signal (307)is provided on the basis of the difference between a sensor signal (306)and a predetermined reference spectre obtained with empty measurementspace (6) and stored in a memory unit (403).